Purpose Development and validation of a fully automated method to detect and quantify
macular fluid in conventional OCT images. Design Development of a diagnostic modality …

Retinal swelling due to the accumulation of fluid is associated with the most vision-
threatening retinal diseases. Optical coherence tomography (OCT) is the current standard of …

Retinal fluid as the major biomarker in exudative macular disease is accurately visualized by
high-resolution three-dimensional optical coherence tomography (OCT), which is used …

Purpose To evaluate the performance of retinal specialists in detecting retinal fluid presence
in spectral domain OCT (SD-OCT) scans from eyes with age-related macular degeneration …

We developed a deep learning algorithm for the automatic segmentation and quantification
of intraretinal cystoid fluid (IRC) in spectral domain optical coherence tomography (SD-OCT) …

Purpose: To investigate quantitative differences in fluid volumes between subretinal fluid
(SRF)–tolerant and SRF-intolerant treat-and-extend regimens for neovascular age-related …

Evaluation of clinical images is essential for diagnosis in many specialties. Therefore the
development of computer vision algorithms to help analyze biomedical images will be …

Purpose: We proposed a deep convolutional neural network (CNN), named Retinal Fluid
Segmentation Network (ReF-Net), to segment retinal fluid in diabetic macular edema (DME) …

As a non-invasive imaging modality, optical coherence tomography (OCT) can provide
micrometer-resolution 3D images of retinal structures. These images can help reveal …

Purpose To evaluate retinal fluid volume data extracted from optical coherence tomography
(OCT) scans by artificial intelligence algorithms in the treatment of neovascular age-related …